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A microservices architecture is the gold standard for building scalable web applications. Gartner estimates that 74% of organizations use microservices for their web applications , with another 23% planning to use them soon.
Dynatrace partners with Texas state institutions Dynatrace partners with public sector agencies in the US and globally to ensure that essential government and educational institutions deliver resilient, efficient, and secure services. Complex IT environments that house these services are often built on hybrid and multicloud architectures.
By embedding Dynatrace AI-driven observability and reliability checks into the deployment pipeline, organizations can proactively assess their cloud architectures against best practices, detecting and resolving potential issues before they impact production.
In this blog we’re going to cover some of the recent, sometimes daily experiences I’ve encountered within Government and Federal agencies to demonstrate the role the Dynatrace platform plays to address these barriers and how agencies can leverage Dynatrace as an invaluable resource that contributes to DevSecOps success.
The Hong Kong Monetary Authority (HKMA)’s Operational Resilience Framework provides guidance for Authorized Institutions (AIs) to ensure the continuity of critical operations during disruptions: governance, risk management, business continuity planning, and oversight of third-party dependencies.
Many organizations are taking a microservices approach to IT architecture. However, in some cases, an organization may be better suited to another architecture approach. Therefore, it’s critical to weigh the advantages of microservices against its potential issues, other architecture approaches, and your unique business needs.
This method of structuring, developing, and operating complex, multi-function software as a collection of smaller independent services is known as microservice architecture. ” it helps to understand the monolithic architectures that preceded them. Understanding monolithic architectures. Microservices benefits.
This method of structuring, developing, and operating complex, multi-function software as a collection of smaller independent services is known as microservice architecture. ” it helps to understand the monolithic architectures that preceded them. Understanding monolithic architectures. Microservices benefits.
A new Dynatrace report highlights the challenges for government and public-sector organizations as they increasingly rely on cloud-native architectures—and a corresponding data explosion. Distributed architectures create another challenge for governments and public-sector organizations.
In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. It’s architecture was specially designed to manage large-scale data warehouses and business intelligence workloads by giving you the ability to spread your data out across a multitude of servers.
Architecture Overview The first pivotal step in managing impressions begins with the creation of a Source-of-Truth (SOT) dataset. Impression Source-of-Truth architecture Ensuring High Quality Impressions Maintaining the highest quality of impressions is a top priority.
State and local governments can prevent outages to improve citizens’ digital experiences Traditional cloud monitoring methods can no longer scale to meet agencies’ demands, as multicloud architectures continue to expand. That’s why teams need a modern observability approach with artificial intelligence at its core.
To drive better outcomes using hybrid cloud architectures, it helps to understand their benefits—and how to orchestrate them seamlessly. What is hybrid cloud architecture? Hybrid cloud architecture is a computing environment that shares data and applications on a combination of public clouds and on-premises private clouds.
While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. This is simply not possible with conventional architectures. Disadvantages.
“To service citizens well, governments will need to be more integrated. William Eggers, Mike Turley, Government Trends 2020, Deloitte Insights, 2019. federal government, IT and program leaders must find a better way to manage their software delivery organizations to improve decision-making where it matters. billion hours.
It starts with implementing data governance practices, which set standards and policies for data use and management in areas such as quality, security, compliance, storage, stewardship, and integration. Modern, cloud-native architectures have many moving parts, and identifying them all is a daunting task with human effort alone.
Overview page of the Pipeline Observability app Thanks to the open and composable platform architecture and the provided toolset, building a custom app that runs natively within Dynatrace was straightforward and efficient.
Want to learn more about how zero trust architecture can improve government user experiences? This episode additionally delves into Sandia’s groundbreaking work in microservices and serverless architecture and their adoption of DevOps and DevSecOps principles.
It also means adapting governance processes and investing in hiring and educating a collaborative workforce who are versed in engineering and operations, and who learn and adapt quickly. Because SRE is a practice, it requires a change in how teams across multiple disciplines communicate, solve problems, and implement solutions.
Government. Government agencies can learn from cause-and-effect relationships to make more evidence-based policy decisions. Some incorporate features for data governance and quality control, which is important for ensuring the accuracy of causal inferences.
It also means adapting governance processes and investing in hiring and educating a collaborative workforce who are versed in engineering and operations, and who learn and adapt quickly. Because SRE is a practice, it requires a change in how teams across multiple disciplines communicate, solve problems, and implement solutions.
US government guidance and fortifying a zero trust architecture with observability – blog Discover the principles of zero-trust architecture and how observability can help government agencies keep their apps secure.
The pandemic has transformed how government agencies such as Health and Human Services (HHS) operate. To learn more or to start a free trial, visit Dynatrace for state and local government. This moves the team away from reactive incident management that contributes to extended outages due to manual escalations.
As a result, Git becomes the single source of truth and control mechanism for creating, updating, and deleting system architecture dynamically. This approach enables teams to apply automation to their testing, delivery, deployment, and governance. Serverless architecture expands. Kubernetes infrastructure evolves.
Our Journey so Far Over the past year, we’ve implemented the core infrastructure pieces necessary for a federated GraphQL architecture as described in our previous post: Studio Edge Architecture The first Domain Graph Service (DGS) on the platform was the former GraphQL monolith that we discussed in our first post (Studio API).
As cloud-native, distributed architectures proliferate, the need for DevOps technologies and DevOps platform engineers has increased as well. Container orchestration platform offering orchestration, automation, security, governance, and other capabilities. CI/CD solution that automates GitOps workflows for cloud-native applications.
Kubernetes has since dominated the market, thanks to “effective evangelism and project governance, attentive development, and a committed community.” Google open-sourced Kubernetes in 2014, positioning it as a competitor to Amazon Web Services, which was already offering open-source software as a service.
Also, these modern, cloud-native architectures produce an immense volume, velocity, and variety of data. This detail and context enable teams to extract relevant information from logs and events to cover custom use cases, like debugging with additional log context, governance audits, platform usage optimization, and many others.
Dynatrace and our local partners helped MAMPU to optimize the digital government experience on several dimensions: Digital Experience: 413% improvement in APDEX, from 0.15 Reducing performance and architectural issues in their backend system gave them a 99% performance improvement! You may ask: How is this possible?
DevOps practices have been established in the last decade to accomplish this goal and deal with the dynamics of modern, cloud-native software architectures. Ensure governance across your organization While Golden Paths are key to bringing DevOps best practices to development teams, distributing them is challenging.
The rapidly evolving digital landscape is one important factor in the acceleration of such transformations – microservices architectures, service mesh, Kubernetes, Functions as a Service (FaaS), and other technologies now enable teams to innovate much faster. New cloud-native technologies make observability more important than ever….
But only 21% said their organizations have established policies governing employees’ use of generative AI technologies. Additionally, blind spots in cloud architecture are making it increasingly difficult for organizations to balance application performance with a robust security posture.
We can also use them for security governance and control, such as pulling images from authorized registries or rejecting deployments that don’t pass security checks. Cloud-native software design, much like microservices architecture, is founded on the premise of speed to delivery via phases, or iterations. Looking ahead.
In today's world, data is generated in high volumes and to make something out of it, extracted data is needed to be transformed, stored, maintained, governed and analyzed. These processes are only possible with a distributed architecture and parallel processing mechanisms that Big Data tools are based on.
The Cloud Operation Competency is earned by AWS partners who offer comprehensive solutions with an integrated approach across all five solution areas of cloud operations: cloud governance, cloud financial management, monitoring and observability, compliance and auditing, and operations management.
As digital transformation accelerates, organizations turn to hybrid and multicloud architectures to innovate, grow, and reduce costs. But the complexity and scale of multicloud architecture invites new enterprise challenges. Protection means securing complex, distributed and high-velocity cloud architectures,” the article continued.
As every company, and government department is pushed to digitally transform, accelerate workloads to the cloud, release better software faster, and then ensure it works perfectly across every customer interaction, the challenge to run this software increases exponentially. IT performance problems increase with cloud-native architectures.
That core, Tay said, is increasingly important to get right with the “plethora of architectures out there.” While 96% of organizations support some level of government regulation surrounding AI, only 2% of companies have self-identified as having fully operationalized responsible AI across their organization.
It also entails secure development practices, security monitoring and logging, compliance and governance, and incident response. Microservices-based architecture Applications built using microservices-based architecture can operate and interact across different cloud platforms. Read report now!
A service mesh is a dedicated infrastructure layer built into an application that controls service-to-service communication in a microservices architecture. It controls the delivery of service requests to other services, performs load balancing, encrypts data, and discovers other services.
All this is easier said than done because: Kubernetes-based dynamic architecture is becoming the norm. Data sovereignty and governance establish compliance standards that regulate or prohibit the collection of certain data in logs. Dynamic landscape and data handling requirements result in manual work.
As more AI-powered technologies are developed and adopted, more government and industry regulations will be enacted. For more information about how explainable AI and increased observability can improve operations, explore the Dynatrace Perform presentation on how major corporations are using Davis AI to manage a microservices architecture.
Legacy technologies involve dependencies, customization, and governance that hamper innovation and create inertia. Successful platform adoption requires a platform to be easy to use and integrate with other architectures, applications, and data sources. Learn more about the Dynatrace platform and its Cloud Done Right architecture.
Change starts by thoroughly evaluating whether the current architecture, tools, and processes for configuration, infrastructure, code delivery pipelines, testing, and monitoring enable improved customer experience faster and with high quality or not. Rethinking the process means digital transformation.
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